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Description
Hi,
After upgrading from v0.12.0 to v0.13.1, I noticed about a 100% slowdown on a pandas-heavy project. I've just started looking, but I've come up with a test case that shows a time-complexity change from O(1) to O(n) (~240x slowdown for my inputs).
Here's the comparison for v0.12.0 (y-axis is milliseconds):
And the comparison for v0.13.1:
The test code (I'll convert this to vbench later):
rows = 1000
columns = 10
data = DataFrame(np.random.random((rows, columns)), index=DatetimeIndex(start='1/1/1900', periods=rows, freq='M'))
d = {}
for col in data:
d[col] = data[col]
%timeit DataFrame(d)
Daily indices don't appear to be affected, though I suspect other frequencies are impacted. I'm seeing similar regressions in v0.13.0.